Process simulation—steady state multiplication

First simulation results on steady state multiplicity of etherification processes were obtained for the MTBE process by Jacobs and Krishna [45] and Nijhuis et al. [78]. These findings attracted considerable interest and triggered further research by others (e. g., [36, 80, 93]). In these papers, a column pressure of 11 bar has been considered, where the process is close to chemical equilibrium. Further, transport processes between vapor, liquid, and catalyst phase as well as transport processes inside the porous catalyst were neglected in a first step. Consequently, the multiplicity is caused by the special properties of the simultaneous phase and reaction equilibrium in such a system and can therefore be explained by means of reactive residue curve maps using oo/< -analysis [34, 35]. A similar type of multiplicity can occur in non-reactive azeotropic distillation [8]. 

Bubble instability is one of the complications of this process. Only recently did this matter receive theoretical attention. As pointed out by Jung and Hyun (28), there are three characteristic bubble instabilities axisymmetric draw resonance, helical instability, and metastability where the bubble alternates between steady states, and the freeze line moves from one position to another. Using linear stability analysis, Cain and Denn (62) showed that multiple steady state solutions are possible for the same set of conditions, as pointed out earlier. However, in order to study the dynamic or time-dependent changes of the process, transient solutions are needed. This was recently achieved by Hyun et al. (65), who succeeded in quite accurately simulating the experimentally observed draw resonance (28). 

An unusual feature of the CD process for MTBE production is that it is recovered from the bottom of the CD column even though its normal boiling point (55°C) is less than the boiling point of methanol (64.5°C). This observation is attributed to the formation of a minimum boiling azeotrope from methanol and MTBE. Apparently, if sufficient quantities of MTBE were accumulated in the CD column, it would lift the methanol into the reaction zone of the column resulting in a higher methanol conversion. This unusual behavior is believed to be responsible for the multiple steady states observed in the MTBE synthesis shown in process simulation and optimization studies and verified experimentally. ... 

The simulator framework CHEOPS couples different simulators at runtime. CHEOPS requires an input file which describes the simulation models and simulators for the components of the overall process, as well as their dependencies. Based on this information, CHEOPS starts the simulators in the correct order. In the case of feedback loops. CHEOPS iterates the simulation runs until a steady state is readied. The input file for CHEOPS is created by an integrator tool which operates on multiple data sources (product management database, integration documents, and the flow diagram). 

Because of the large multiplicity regions, multiple steady states of the TAME process were also verified experimentally as illustrated in Fig. 10.15 [71, 73, 85). For this purpose suitable startup strategies were developed by means of dynamic simulation to operate the column directly into the desired steady state. Further, it was... 

The influence of capillary condensation upon catalyst effectiveness factor has been assessed both by approximate calculations and by pore network simulations. It was found that catalyst effectiveness could be affected by the presence of capillary condensation, depending on the ratio of reaction rates in the gas and liquid phases. The effectiveness factor under conditions of capillary condensation is sensitive to operating conditions of the reactor, such as pressure, and to properties of the catalyst pore structure like pore-size distribution and connectivity. Once the catalyst pellet contains some pores filled with liquid, the kinetics of the process become dependent upon the phase equilibria of the system. This can lead to multiple steady states in the reaction rate as a function of temperature or pressure, because the current state of the catalyst pellet depends on the history of temperature and pressure profiles to which it has been subjected. 

Space 6. Behavior analysis steady state simulations are carried out to explore the kinetics, gas/liquid mass transfer, hydrodynamics and multiplicities inside the units. Dynamic simulations are performed to check the robustness of the design, in terms of the ability to maintain product purities and conversion in a desired range when disturbances occur. If the process is controllable and economically attractive at the estimated operating conditions, go to the next... 

It is the model library for fixed-bed catalytic reaction, fluidised-bed and various polymer reactors and so on. Different tools are available in gPROMS software for simulation and modelling of various systems. Some of the following are (i) multi-scale modelling of complex processes and phenomena, (ii) State-of-the-art model validation tools allow estimation of multiple model parameters from steady-state and dynamic experimental data, and provide rigorous model-based data analysis, (iii) The maximum amount of parameter information from the minimum number of experiments, (iv) The gPROMS-CFD Hybrid Multitubular interface provides ultimate accuracy in the modelling of... 

Two basic approaches can be adopted for using fixed beds to simulate the operation of moving beds. In the first, multiple fixed beds are used in cascade, as shown in Figure 5.12 (and described later in Section 7.7.1) to gain most of the benefit of a continuous steady state countercurrent process. The concept is similar to that used in the pulsed bed. At each switch in the cascade a fully regenerated bed is added to the outlet end of a sequence of beds in series when breakthrough is about to occur. At the same time the... 

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